Applied Statistics with R by David Dalpiaz
Book Contents :-
1. Introduction
2. Introduction to R
3. Data and Programming
4. Summarizing Data
5. Probability and Statistics in R
6. R Resources
7. Simple Linear Regression
8. Inference for Simple Linear Regression
9. Multiple Linear Regression
10. Model Building
11. Categorical Predictors and Interactions
12. Analysis of Variance
13. Model Diagnostics
14. Transformations
15. Collinearity
16. Variable Selection and Model Building
17. Logistic Regression
18. Beyond
About this book :-
"Applied Statistics with R" by David Dalpiaz is a practical guide for learning how to apply "statistics" using the "R programming language". The book focuses on real-world applications, helping readers understand how to explore, analyze, and interpret data in a meaningful way. It balances foundational theory with hands-on examples, making it accessible to students, researchers, and professionals new to statistical analysis.
The book covers key topics in applied statistics, including "descriptive statistics", probability distributions, hypothesis testing, regression analysis, and ANOVA. Each method is explained with practical examples and implemented in R, allowing readers to see how statistical techniques work in real datasets. The emphasis on reproducible R code helps readers develop both analytical and computational skills, while reinforcing concepts with visualizations and outputs.
Overall, this book is ideal for learners who want to apply "data analysis", "regression modeling", "data visualization", "R programming", and applied statistical techniques to real-world problems. By combining theory, code, and practical examples, it equips readers with the skills needed to perform thorough statistical analyses, generate insights from data, and make data-driven decisions with confidence. It is a valuable resource for students, analysts, and anyone seeking a hands-on introduction to applied statistics with R.
Book Detail :-
Title:
Applied Statistics with R by David Dalpiaz
Publisher:
Self Publishing
Year:
2021
Pages:
457
Type:
PDF
Language:
English
ISBN-10 #:
0198869975
ISBN-13 #:
978-0198869979
License:
CC BY-NC-SA 4.0
Amazon:
Amazon
About Author :-
The author
David Dalpiaz
is an American statistician and educator based at the "University of Illinois Urbana-Champaign". He earned his "BS, MS, and PhD in Statistics" from the same institution, building a strong foundation in mathematical and applied statistics. Dalpiaz focuses on teaching and making statistical concepts accessible to students across disciplines. His expertise includes "applied statistics, R programming, statistical modeling, data analysis, and pedagogy". He authors practical resources like "Applied Statistics with R" and "Atomic R", emphasizing real-world applications and hands-on learning. Dalpiaz’s work helps students and researchers apply statistical techniques effectively using R in diverse scientific and professional contexts.
Similar
Regression & Statistical Learning
Books